Overview

Dataset statistics

Number of variables44
Number of observations40336
Missing cells509176
Missing cells (%)28.7%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory13.5 MiB
Average record size in memory352.0 B

Variable types

Numeric39
Categorical5

Alerts

SBP is highly correlated with MAP and 1 other fieldsHigh correlation
MAP is highly correlated with SBP and 1 other fieldsHigh correlation
DBP is highly correlated with SBP and 1 other fieldsHigh correlation
BaseExcess is highly correlated with HCO3 and 1 other fieldsHigh correlation
HCO3 is highly correlated with BaseExcess and 1 other fieldsHigh correlation
pH is highly correlated with BaseExcessHigh correlation
PaCO2 is highly correlated with HCO3High correlation
AST is highly correlated with Bilirubin_directHigh correlation
BUN is highly correlated with CreatinineHigh correlation
Creatinine is highly correlated with BUNHigh correlation
Bilirubin_direct is highly correlated with AST and 1 other fieldsHigh correlation
Bilirubin_total is highly correlated with Bilirubin_directHigh correlation
Hct is highly correlated with HgbHigh correlation
Hgb is highly correlated with HctHigh correlation
Unit1 is highly correlated with Unit2High correlation
Unit2 is highly correlated with Unit1High correlation
SBP is highly correlated with MAP and 1 other fieldsHigh correlation
MAP is highly correlated with SBP and 1 other fieldsHigh correlation
DBP is highly correlated with SBP and 1 other fieldsHigh correlation
BaseExcess is highly correlated with HCO3 and 2 other fieldsHigh correlation
HCO3 is highly correlated with BaseExcess and 1 other fieldsHigh correlation
pH is highly correlated with BaseExcessHigh correlation
PaCO2 is highly correlated with BaseExcess and 1 other fieldsHigh correlation
BUN is highly correlated with Creatinine and 1 other fieldsHigh correlation
Creatinine is highly correlated with BUN and 1 other fieldsHigh correlation
Bilirubin_direct is highly correlated with Bilirubin_totalHigh correlation
Phosphate is highly correlated with BUN and 1 other fieldsHigh correlation
Bilirubin_total is highly correlated with Bilirubin_directHigh correlation
Hct is highly correlated with HgbHigh correlation
Hgb is highly correlated with HctHigh correlation
Unit1 is highly correlated with Unit2High correlation
Unit2 is highly correlated with Unit1High correlation
SBP is highly correlated with MAPHigh correlation
MAP is highly correlated with SBP and 1 other fieldsHigh correlation
DBP is highly correlated with MAPHigh correlation
BaseExcess is highly correlated with HCO3 and 1 other fieldsHigh correlation
HCO3 is highly correlated with BaseExcessHigh correlation
pH is highly correlated with BaseExcessHigh correlation
BUN is highly correlated with CreatinineHigh correlation
Creatinine is highly correlated with BUNHigh correlation
Bilirubin_direct is highly correlated with Bilirubin_totalHigh correlation
Bilirubin_total is highly correlated with Bilirubin_directHigh correlation
Hct is highly correlated with HgbHigh correlation
Hgb is highly correlated with HctHigh correlation
Unit1 is highly correlated with Unit2High correlation
Unit2 is highly correlated with Unit1High correlation
Unit2 is highly correlated with Unit1High correlation
Unit1 is highly correlated with Unit2High correlation
DBP has 7411 (18.4%) missing values Missing
EtCO2 has 37120 (92.0%) missing values Missing
BaseExcess has 27126 (67.3%) missing values Missing
HCO3 has 20119 (49.9%) missing values Missing
FiO2 has 22527 (55.8%) missing values Missing
pH has 21401 (53.1%) missing values Missing
PaCO2 has 21980 (54.5%) missing values Missing
SaO2 has 27248 (67.6%) missing values Missing
AST has 25979 (64.4%) missing values Missing
BUN has 2018 (5.0%) missing values Missing
Alkalinephos has 26163 (64.9%) missing values Missing
Calcium has 5339 (13.2%) missing values Missing
Chloride has 18925 (46.9%) missing values Missing
Creatinine has 2049 (5.1%) missing values Missing
Bilirubin_direct has 38279 (94.9%) missing values Missing
Glucose has 1580 (3.9%) missing values Missing
Lactate has 27843 (69.0%) missing values Missing
Magnesium has 4931 (12.2%) missing values Missing
Phosphate has 12015 (29.8%) missing values Missing
Potassium has 1867 (4.6%) missing values Missing
Bilirubin_total has 26088 (64.7%) missing values Missing
TroponinI has 33283 (82.5%) missing values Missing
Hct has 2317 (5.7%) missing values Missing
Hgb has 2448 (6.1%) missing values Missing
PTT has 20098 (49.8%) missing values Missing
WBC has 2625 (6.5%) missing values Missing
Fibrinogen has 35821 (88.8%) missing values Missing
Platelets has 2577 (6.4%) missing values Missing
Unit1 has 15617 (38.7%) missing values Missing
Unit2 has 15617 (38.7%) missing values Missing
FiO2 is highly skewed (γ1 = -81.07615775) Skewed
ICULOS is highly skewed (γ1 = 77.93149665) Skewed
PatientID has unique values Unique
BaseExcess has 2279 (5.7%) zeros Zeros
HospAdmTime has 1313 (3.3%) zeros Zeros

Reproduction

Analysis started2021-11-29 10:27:10.332688
Analysis finished2021-11-29 10:27:22.885779
Duration12.55 seconds
Software versionpandas-profiling v3.1.1
Download configurationconfig.json

Variables

PatientID
Real number (ℝ≥0)

UNIQUE

Distinct40336
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean59671.27286
Minimum1
Maximum120000
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size315.2 KiB
2021-11-29T11:27:22.930749image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile2017.75
Q110084.75
median20475.5
Q3109916.25
95-th percentile117983.25
Maximum120000
Range119999
Interquartile range (IQR)99831.5

Descriptive statistics

Standard deviation50251.33712
Coefficient of variation (CV)0.842136169
Kurtosis-1.946653503
Mean59671.27286
Median Absolute Deviation (MAD)20307
Skewness0.01560297418
Sum2406900462
Variance2525196883
MonotonicityStrictly increasing
2021-11-29T11:27:23.036090image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
11
 
< 0.1%
1065591
 
< 0.1%
1065521
 
< 0.1%
1065531
 
< 0.1%
1065541
 
< 0.1%
1065551
 
< 0.1%
1065561
 
< 0.1%
1065571
 
< 0.1%
1065581
 
< 0.1%
1065601
 
< 0.1%
Other values (40326)40326
> 99.9%
ValueCountFrequency (%)
11
< 0.1%
21
< 0.1%
31
< 0.1%
41
< 0.1%
51
< 0.1%
61
< 0.1%
71
< 0.1%
81
< 0.1%
91
< 0.1%
101
< 0.1%
ValueCountFrequency (%)
1200001
< 0.1%
1199991
< 0.1%
1199981
< 0.1%
1199971
< 0.1%
1199961
< 0.1%
1199951
< 0.1%
1199941
< 0.1%
1199931
< 0.1%
1199921
< 0.1%
1199911
< 0.1%

HR
Real number (ℝ≥0)

Distinct214
Distinct (%)0.5%
Missing5
Missing (%)< 0.1%
Infinite0
Infinite (%)0.0%
Mean69.65462052
Minimum20
Maximum154.5
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size315.2 KiB
2021-11-29T11:27:23.140834image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Quantile statistics

Minimum20
5-th percentile49
Q160
median69
Q378
95-th percentile94
Maximum154.5
Range134.5
Interquartile range (IQR)18

Descriptive statistics

Standard deviation13.85867914
Coefficient of variation (CV)0.1989628116
Kurtosis0.5707377749
Mean69.65462052
Median Absolute Deviation (MAD)9
Skewness0.4224599554
Sum2809240.5
Variance192.0629875
MonotonicityNot monotonic
2021-11-29T11:27:23.247491image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
601554
 
3.9%
701353
 
3.4%
681280
 
3.2%
621170
 
2.9%
661148
 
2.8%
641131
 
2.8%
721070
 
2.7%
801032
 
2.6%
741013
 
2.5%
651004
 
2.5%
Other values (204)28576
70.8%
ValueCountFrequency (%)
204
< 0.1%
213
< 0.1%
224
< 0.1%
232
 
< 0.1%
23.51
 
< 0.1%
242
 
< 0.1%
255
< 0.1%
263
< 0.1%
26.51
 
< 0.1%
275
< 0.1%
ValueCountFrequency (%)
154.51
< 0.1%
1461
< 0.1%
1441
< 0.1%
1401
< 0.1%
1371
< 0.1%
1361
< 0.1%
1351
< 0.1%
134.51
< 0.1%
1341
< 0.1%
133.51
< 0.1%

O2Sat
Real number (ℝ≥0)

Distinct136
Distinct (%)0.3%
Missing18
Missing (%)< 0.1%
Infinite0
Infinite (%)0.0%
Mean91.91585644
Minimum20
Maximum100
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size315.2 KiB
2021-11-29T11:27:23.356000image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Quantile statistics

Minimum20
5-th percentile83
Q191
median93
Q395
95-th percentile98
Maximum100
Range80
Interquartile range (IQR)4

Descriptive statistics

Standard deviation6.725975045
Coefficient of variation (CV)0.07317535086
Kurtosis34.44560217
Mean91.91585644
Median Absolute Deviation (MAD)2
Skewness-4.774912602
Sum3705863.5
Variance45.23874031
MonotonicityNot monotonic
2021-11-29T11:27:23.455751image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
944856
12.0%
934727
11.7%
924358
10.8%
954353
10.8%
963400
8.4%
913094
 
7.7%
902415
 
6.0%
972295
 
5.7%
981307
 
3.2%
891275
 
3.2%
Other values (126)8238
20.4%
ValueCountFrequency (%)
2014
< 0.1%
216
< 0.1%
229
< 0.1%
235
 
< 0.1%
248
< 0.1%
253
 
< 0.1%
267
< 0.1%
276
< 0.1%
288
< 0.1%
296
< 0.1%
ValueCountFrequency (%)
100349
 
0.9%
99.541
 
0.1%
99640
 
1.6%
98.565
 
0.2%
981307
 
3.2%
97.5118
 
0.3%
972295
5.7%
96.5172
 
0.4%
963400
8.4%
95.5207
 
0.5%

Temp
Real number (ℝ≥0)

Distinct327
Distinct (%)0.8%
Missing284
Missing (%)0.7%
Infinite0
Infinite (%)0.0%
Mean36.07429616
Minimum20.9
Maximum39.33
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size315.2 KiB
2021-11-29T11:27:23.562412image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Quantile statistics

Minimum20.9
5-th percentile35.06
Q135.7
median36.1
Q336.5
95-th percentile37
Maximum39.33
Range18.43
Interquartile range (IQR)0.8

Descriptive statistics

Standard deviation0.6855312438
Coefficient of variation (CV)0.01900331584
Kurtosis29.37012616
Mean36.07429616
Median Absolute Deviation (MAD)0.4
Skewness-2.326754768
Sum1444847.71
Variance0.4699530863
MonotonicityNot monotonic
2021-11-29T11:27:23.663350image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
362913
 
7.2%
36.51824
 
4.5%
36.21537
 
3.8%
36.41518
 
3.8%
36.31416
 
3.5%
36.11389
 
3.4%
35.91271
 
3.2%
35.81192
 
3.0%
36.111168
 
2.9%
35.51058
 
2.6%
Other values (317)24766
61.4%
ValueCountFrequency (%)
20.91
 
< 0.1%
211
 
< 0.1%
231
 
< 0.1%
23.61
 
< 0.1%
26.61
 
< 0.1%
26.675
< 0.1%
281
 
< 0.1%
29.61
 
< 0.1%
29.611
 
< 0.1%
29.81
 
< 0.1%
ValueCountFrequency (%)
39.331
 
< 0.1%
39.21
 
< 0.1%
39.171
 
< 0.1%
39.111
 
< 0.1%
39.11
 
< 0.1%
38.891
 
< 0.1%
38.831
 
< 0.1%
38.83
< 0.1%
38.781
 
< 0.1%
38.73
< 0.1%

SBP
Real number (ℝ≥0)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION

Distinct393
Distinct (%)1.0%
Missing282
Missing (%)0.7%
Infinite0
Infinite (%)0.0%
Mean97.20425351
Minimum20
Maximum190
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size315.2 KiB
2021-11-29T11:27:23.769514image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Quantile statistics

Minimum20
5-th percentile73.5
Q187
median95
Q3106.5
95-th percentile127.5
Maximum190
Range170
Interquartile range (IQR)19.5

Descriptive statistics

Standard deviation16.72265311
Coefficient of variation (CV)0.1720362279
Kurtosis1.331382014
Mean97.20425351
Median Absolute Deviation (MAD)10
Skewness0.3952624199
Sum3893419.17
Variance279.647127
MonotonicityNot monotonic
2021-11-29T11:27:23.862103image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
901334
 
3.3%
911174
 
2.9%
921171
 
2.9%
941131
 
2.8%
931075
 
2.7%
95990
 
2.5%
96960
 
2.4%
97949
 
2.4%
89937
 
2.3%
98933
 
2.3%
Other values (383)29400
72.9%
ValueCountFrequency (%)
204
< 0.1%
212
 
< 0.1%
226
< 0.1%
23.51
 
< 0.1%
245
< 0.1%
255
< 0.1%
262
 
< 0.1%
272
 
< 0.1%
27.51
 
< 0.1%
283
< 0.1%
ValueCountFrequency (%)
1901
< 0.1%
1871
< 0.1%
1831
< 0.1%
1811
< 0.1%
1802
< 0.1%
178.51
< 0.1%
1761
< 0.1%
1741
< 0.1%
1721
< 0.1%
1711
< 0.1%

MAP
Real number (ℝ≥0)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION

Distinct428
Distinct (%)1.1%
Missing104
Missing (%)0.3%
Infinite0
Infinite (%)0.0%
Mean64.57407611
Minimum20
Maximum140
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size315.2 KiB
2021-11-29T11:27:24.045855image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Quantile statistics

Minimum20
5-th percentile46
Q157
median63
Q372
95-th percentile87
Maximum140
Range120
Interquartile range (IQR)15

Descriptive statistics

Standard deviation12.63975685
Coefficient of variation (CV)0.1957404211
Kurtosis1.198004199
Mean64.57407611
Median Absolute Deviation (MAD)7
Skewness0.4357847718
Sum2597944.23
Variance159.7634533
MonotonicityNot monotonic
2021-11-29T11:27:24.145182image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
601374
 
3.4%
621372
 
3.4%
641322
 
3.3%
611310
 
3.2%
631241
 
3.1%
581215
 
3.0%
591130
 
2.8%
661112
 
2.8%
651103
 
2.7%
681083
 
2.7%
Other values (418)27970
69.3%
ValueCountFrequency (%)
2019
< 0.1%
20.331
 
< 0.1%
20.52
 
< 0.1%
217
 
< 0.1%
21.331
 
< 0.1%
21.51
 
< 0.1%
2215
< 0.1%
22.53
 
< 0.1%
2312
< 0.1%
23.51
 
< 0.1%
ValueCountFrequency (%)
1401
< 0.1%
1361
< 0.1%
1301
< 0.1%
1292
< 0.1%
1261
< 0.1%
1252
< 0.1%
1241
< 0.1%
1231
< 0.1%
122.52
< 0.1%
1222
< 0.1%

DBP
Real number (ℝ≥0)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
MISSING

Distinct192
Distinct (%)0.6%
Missing7411
Missing (%)18.4%
Infinite0
Infinite (%)0.0%
Mean50.2514044
Minimum20
Maximum134
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size315.2 KiB
2021-11-29T11:27:24.242975image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Quantile statistics

Minimum20
5-th percentile34.5
Q143.5
median50
Q356
95-th percentile69
Maximum134
Range114
Interquartile range (IQR)12.5

Descriptive statistics

Standard deviation10.38313907
Coefficient of variation (CV)0.2066238585
Kurtosis1.033972871
Mean50.2514044
Median Absolute Deviation (MAD)6
Skewness0.4665701875
Sum1654527.49
Variance107.809577
MonotonicityNot monotonic
2021-11-29T11:27:24.344880image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
501575
 
3.9%
521343
 
3.3%
481335
 
3.3%
511314
 
3.3%
461270
 
3.1%
441243
 
3.1%
491160
 
2.9%
471133
 
2.8%
451118
 
2.8%
531117
 
2.8%
Other values (182)20317
50.4%
(Missing)7411
 
18.4%
ValueCountFrequency (%)
2029
0.1%
20.54
 
< 0.1%
2120
< 0.1%
21.56
 
< 0.1%
2227
0.1%
22.51
 
< 0.1%
2338
0.1%
23.251
 
< 0.1%
23.52
 
< 0.1%
2445
0.1%
ValueCountFrequency (%)
1341
 
< 0.1%
1171
 
< 0.1%
1091
 
< 0.1%
1081
 
< 0.1%
1052
 
< 0.1%
100.51
 
< 0.1%
981
 
< 0.1%
972
 
< 0.1%
963
< 0.1%
956
< 0.1%

Resp
Real number (ℝ≥0)

Distinct87
Distinct (%)0.2%
Missing71
Missing (%)0.2%
Infinite0
Infinite (%)0.0%
Mean12.55075723
Minimum1
Maximum35
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size315.2 KiB
2021-11-29T11:27:24.448355image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile7
Q110
median12
Q315
95-th percentile18
Maximum35
Range34
Interquartile range (IQR)5

Descriptive statistics

Standard deviation3.507440418
Coefficient of variation (CV)0.2794604623
Kurtosis1.491944718
Mean12.55075723
Median Absolute Deviation (MAD)2
Skewness-0.006659246793
Sum505356.24
Variance12.30213829
MonotonicityNot monotonic
2021-11-29T11:27:24.546579image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
126342
15.7%
104752
11.8%
144727
11.7%
163543
8.8%
113437
8.5%
133172
7.9%
152785
6.9%
91862
 
4.6%
81537
 
3.8%
181506
 
3.7%
Other values (77)6602
16.4%
ValueCountFrequency (%)
1246
0.6%
1.518
 
< 0.1%
2191
0.5%
2.519
 
< 0.1%
3159
0.4%
3.513
 
< 0.1%
3.841
 
< 0.1%
4168
0.4%
4.57
 
< 0.1%
5230
0.6%
ValueCountFrequency (%)
352
 
< 0.1%
342
 
< 0.1%
331
 
< 0.1%
324
 
< 0.1%
312
 
< 0.1%
305
 
< 0.1%
295
 
< 0.1%
28.51
 
< 0.1%
2816
< 0.1%
27.51
 
< 0.1%

EtCO2
Real number (ℝ≥0)

MISSING

Distinct91
Distinct (%)2.8%
Missing37120
Missing (%)92.0%
Infinite0
Infinite (%)0.0%
Mean28.01912313
Minimum10
Maximum100
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size315.2 KiB
2021-11-29T11:27:24.652141image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Quantile statistics

Minimum10
5-th percentile12
Q122
median28
Q333
95-th percentile39.5
Maximum100
Range90
Interquartile range (IQR)11

Descriptive statistics

Standard deviation11.00698314
Coefficient of variation (CV)0.3928382442
Kurtosis16.56850982
Mean28.01912313
Median Absolute Deviation (MAD)5.5
Skewness2.812296261
Sum90109.5
Variance121.1536777
MonotonicityNot monotonic
2021-11-29T11:27:24.748967image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
30155
 
0.4%
28145
 
0.4%
32130
 
0.3%
24128
 
0.3%
29128
 
0.3%
26123
 
0.3%
31121
 
0.3%
27113
 
0.3%
34111
 
0.3%
25109
 
0.3%
Other values (81)1953
 
4.8%
(Missing)37120
92.0%
ValueCountFrequency (%)
1075
0.2%
10.513
 
< 0.1%
1131
0.1%
11.58
 
< 0.1%
1242
0.1%
12.59
 
< 0.1%
1340
0.1%
13.510
 
< 0.1%
1431
0.1%
14.511
 
< 0.1%
ValueCountFrequency (%)
1007
< 0.1%
994
< 0.1%
986
< 0.1%
979
< 0.1%
963
 
< 0.1%
951
 
< 0.1%
942
 
< 0.1%
932
 
< 0.1%
924
< 0.1%
861
 
< 0.1%

BaseExcess
Real number (ℝ)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
MISSING
ZEROS

Distinct259
Distinct (%)2.0%
Missing27126
Missing (%)67.3%
Infinite0
Infinite (%)0.0%
Mean-2.362978804
Minimum-32
Maximum25
Zeros2279
Zeros (%)5.7%
Negative8592
Negative (%)21.3%
Memory size315.2 KiB
2021-11-29T11:27:24.847606image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Quantile statistics

Minimum-32
5-th percentile-10
Q1-5
median-2
Q30
95-th percentile4
Maximum25
Range57
Interquartile range (IQR)5

Descriptive statistics

Standard deviation4.570287145
Coefficient of variation (CV)-1.934121092
Kurtosis4.009071009
Mean-2.362978804
Median Absolute Deviation (MAD)2
Skewness-0.6233027456
Sum-31214.95
Variance20.88752459
MonotonicityNot monotonic
2021-11-29T11:27:24.940580image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
02279
 
5.7%
-21341
 
3.3%
-31262
 
3.1%
-11246
 
3.1%
-41013
 
2.5%
-5829
 
2.1%
-6615
 
1.5%
1589
 
1.5%
2459
 
1.1%
-7424
 
1.1%
Other values (249)3153
 
7.8%
(Missing)27126
67.3%
ValueCountFrequency (%)
-321
 
< 0.1%
-301
 
< 0.1%
-292
 
< 0.1%
-282
 
< 0.1%
-275
< 0.1%
-26.51
 
< 0.1%
-264
< 0.1%
-25.51
 
< 0.1%
-257
< 0.1%
-249
< 0.1%
ValueCountFrequency (%)
251
 
< 0.1%
231
 
< 0.1%
211
 
< 0.1%
201
 
< 0.1%
192
 
< 0.1%
183
 
< 0.1%
175
< 0.1%
1610
< 0.1%
155
< 0.1%
148
< 0.1%

HCO3
Real number (ℝ≥0)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
MISSING

Distinct205
Distinct (%)1.0%
Missing20119
Missing (%)49.9%
Infinite0
Infinite (%)0.0%
Mean23.15542613
Minimum0
Maximum53
Zeros2
Zeros (%)< 0.1%
Negative0
Negative (%)0.0%
Memory size315.2 KiB
2021-11-29T11:27:25.041380image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile16
Q121
median23
Q325.4
95-th percentile30
Maximum53
Range53
Interquartile range (IQR)4.4

Descriptive statistics

Standard deviation4.261534835
Coefficient of variation (CV)0.184040441
Kurtosis2.616114142
Mean23.15542613
Median Absolute Deviation (MAD)2
Skewness0.04858483908
Sum468133.25
Variance18.16067915
MonotonicityNot monotonic
2021-11-29T11:27:25.141756image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
242386
 
5.9%
232367
 
5.9%
222129
 
5.3%
251995
 
4.9%
211626
 
4.0%
261593
 
3.9%
201253
 
3.1%
271146
 
2.8%
19895
 
2.2%
28711
 
1.8%
Other values (195)4116
 
10.2%
(Missing)20119
49.9%
ValueCountFrequency (%)
02
 
< 0.1%
510
 
< 0.1%
617
 
< 0.1%
79
 
< 0.1%
7.71
 
< 0.1%
831
0.1%
8.41
 
< 0.1%
931
0.1%
1050
0.1%
10.51
 
< 0.1%
ValueCountFrequency (%)
531
 
< 0.1%
502
 
< 0.1%
472
 
< 0.1%
462
 
< 0.1%
454
 
< 0.1%
444
 
< 0.1%
437
 
< 0.1%
429
< 0.1%
418
< 0.1%
4018
< 0.1%

FiO2
Real number (ℝ)

MISSING
SKEWED

Distinct82
Distinct (%)0.5%
Missing22527
Missing (%)55.8%
Infinite0
Infinite (%)0.0%
Mean0.4304548262
Minimum-50
Maximum10
Zeros64
Zeros (%)0.2%
Negative2
Negative (%)< 0.1%
Memory size315.2 KiB
2021-11-29T11:27:25.239441image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Quantile statistics

Minimum-50
5-th percentile0.21
Q10.4
median0.4
Q30.5
95-th percentile0.7
Maximum10
Range60
Interquartile range (IQR)0.1

Descriptive statistics

Standard deviation0.5614511943
Coefficient of variation (CV)1.304320826
Kurtosis7314.619527
Mean0.4304548262
Median Absolute Deviation (MAD)0.05
Skewness-81.07615775
Sum7665.97
Variance0.3152274436
MonotonicityNot monotonic
2021-11-29T11:27:25.335819image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.48145
 
20.2%
0.53914
 
9.7%
0.351106
 
2.7%
0.21814
 
2.0%
0.3746
 
1.8%
1640
 
1.6%
0.6428
 
1.1%
0.28328
 
0.8%
0.7288
 
0.7%
0.45236
 
0.6%
Other values (72)1164
 
2.9%
(Missing)22527
55.8%
ValueCountFrequency (%)
-502
 
< 0.1%
064
0.2%
0.011
 
< 0.1%
0.0236
0.1%
0.0323
 
0.1%
0.0455
0.1%
0.0520
 
< 0.1%
0.0615
 
< 0.1%
0.084
 
< 0.1%
0.14
 
< 0.1%
ValueCountFrequency (%)
101
 
< 0.1%
24
 
< 0.1%
1.21
 
< 0.1%
1640
1.6%
0.993
 
< 0.1%
0.987
 
< 0.1%
0.962
 
< 0.1%
0.9542
 
0.1%
0.941
 
< 0.1%
0.931
 
< 0.1%

pH
Real number (ℝ≥0)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
MISSING

Distinct91
Distinct (%)0.5%
Missing21401
Missing (%)53.1%
Infinite0
Infinite (%)0.0%
Mean7.339229469
Minimum6.62
Maximum7.73
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size315.2 KiB
2021-11-29T11:27:25.517745image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Quantile statistics

Minimum6.62
5-th percentile7.2
Q17.3
median7.35
Q37.39
95-th percentile7.46
Maximum7.73
Range1.11
Interquartile range (IQR)0.09

Descriptive statistics

Standard deviation0.08416769452
Coefficient of variation (CV)0.01146819225
Kurtosis4.613143098
Mean7.339229469
Median Absolute Deviation (MAD)0.05
Skewness-1.159525453
Sum138968.31
Variance0.0070842008
MonotonicityNot monotonic
2021-11-29T11:27:25.616388image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
7.361162
 
2.9%
7.341118
 
2.8%
7.351075
 
2.7%
7.321062
 
2.6%
7.371023
 
2.5%
7.381012
 
2.5%
7.33982
 
2.4%
7.31888
 
2.2%
7.4873
 
2.2%
7.39835
 
2.1%
Other values (81)8905
22.1%
(Missing)21401
53.1%
ValueCountFrequency (%)
6.621
 
< 0.1%
6.631
 
< 0.1%
6.651
 
< 0.1%
6.711
 
< 0.1%
6.721
 
< 0.1%
6.731
 
< 0.1%
6.782
< 0.1%
6.791
 
< 0.1%
6.813
< 0.1%
6.824
< 0.1%
ValueCountFrequency (%)
7.731
 
< 0.1%
7.661
 
< 0.1%
7.631
 
< 0.1%
7.612
 
< 0.1%
7.64
 
< 0.1%
7.594
 
< 0.1%
7.583
 
< 0.1%
7.575
 
< 0.1%
7.5611
< 0.1%
7.5514
< 0.1%

PaCO2
Real number (ℝ≥0)

HIGH CORRELATION
HIGH CORRELATION
MISSING

Distinct381
Distinct (%)2.1%
Missing21980
Missing (%)54.5%
Infinite0
Infinite (%)0.0%
Mean36.92621486
Minimum10
Maximum100
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size315.2 KiB
2021-11-29T11:27:25.721649image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Quantile statistics

Minimum10
5-th percentile26
Q132
median36
Q341
95-th percentile51
Maximum100
Range90
Interquartile range (IQR)9

Descriptive statistics

Standard deviation8.380026293
Coefficient of variation (CV)0.2269397588
Kurtosis5.91974179
Mean36.92621486
Median Absolute Deviation (MAD)4
Skewness1.512382669
Sum677817.6
Variance70.22484067
MonotonicityNot monotonic
2021-11-29T11:27:25.814955image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
361083
 
2.7%
341054
 
2.6%
351023
 
2.5%
38995
 
2.5%
37986
 
2.4%
32938
 
2.3%
33908
 
2.3%
39794
 
2.0%
40794
 
2.0%
31773
 
1.9%
Other values (371)9008
22.3%
(Missing)21980
54.5%
ValueCountFrequency (%)
101
 
< 0.1%
113
 
< 0.1%
123
 
< 0.1%
133
 
< 0.1%
144
 
< 0.1%
1513
< 0.1%
15.31
 
< 0.1%
1615
< 0.1%
16.21
 
< 0.1%
16.42
 
< 0.1%
ValueCountFrequency (%)
1001
 
< 0.1%
952
< 0.1%
942
< 0.1%
93.41
 
< 0.1%
932
< 0.1%
911
 
< 0.1%
89.51
 
< 0.1%
893
< 0.1%
88.11
 
< 0.1%
882
< 0.1%

SaO2
Real number (ℝ≥0)

MISSING

Distinct364
Distinct (%)2.8%
Missing27248
Missing (%)67.6%
Infinite0
Infinite (%)0.0%
Mean88.66616748
Minimum23
Maximum100
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size315.2 KiB
2021-11-29T11:27:25.913520image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Quantile statistics

Minimum23
5-th percentile58
Q185
median95.8
Q397.9
95-th percentile99
Maximum100
Range77
Interquartile range (IQR)12.9

Descriptive statistics

Standard deviation14.03873552
Coefficient of variation (CV)0.158332495
Kurtosis1.375172105
Mean88.66616748
Median Absolute Deviation (MAD)2.4
Skewness-1.562862534
Sum1160462.8
Variance197.0860949
MonotonicityNot monotonic
2021-11-29T11:27:26.017559image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
981392
 
3.5%
971140
 
2.8%
96741
 
1.8%
95451
 
1.1%
99422
 
1.0%
94361
 
0.9%
93227
 
0.6%
92155
 
0.4%
63129
 
0.3%
98.8120
 
0.3%
Other values (354)7950
 
19.7%
(Missing)27248
67.6%
ValueCountFrequency (%)
231
 
< 0.1%
241
 
< 0.1%
261
 
< 0.1%
272
< 0.1%
281
 
< 0.1%
293
< 0.1%
29.11
 
< 0.1%
304
< 0.1%
311
 
< 0.1%
322
< 0.1%
ValueCountFrequency (%)
10019
 
< 0.1%
99.930
0.1%
99.838
0.1%
99.748
0.1%
99.654
0.1%
99.552
 
< 0.1%
99.564
0.2%
99.452
 
< 0.1%
99.471
0.2%
99.358
0.1%

AST
Real number (ℝ≥0)

HIGH CORRELATION
MISSING

Distinct851
Distinct (%)5.9%
Missing25979
Missing (%)64.4%
Infinite0
Infinite (%)0.0%
Mean98.94702932
Minimum3
Maximum9210
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size315.2 KiB
2021-11-29T11:27:26.124625image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Quantile statistics

Minimum3
5-th percentile13
Q120
median31
Q361
95-th percentile319.2
Maximum9210
Range9207
Interquartile range (IQR)41

Descriptive statistics

Standard deviation353.2283957
Coefficient of variation (CV)3.56987368
Kurtosis203.0301688
Mean98.94702932
Median Absolute Deviation (MAD)14
Skewness12.29490508
Sum1420582.5
Variance124770.2996
MonotonicityNot monotonic
2021-11-29T11:27:26.223317image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
17486
 
1.2%
18455
 
1.1%
19448
 
1.1%
16439
 
1.1%
20429
 
1.1%
21416
 
1.0%
15396
 
1.0%
24390
 
1.0%
22389
 
1.0%
14366
 
0.9%
Other values (841)10143
 
25.1%
(Missing)25979
64.4%
ValueCountFrequency (%)
32
 
< 0.1%
41
 
< 0.1%
511
 
< 0.1%
5.51
 
< 0.1%
614
 
< 0.1%
715
 
< 0.1%
843
 
0.1%
963
 
0.2%
10122
0.3%
11181
0.4%
ValueCountFrequency (%)
92101
< 0.1%
85911
< 0.1%
85671
< 0.1%
79061
< 0.1%
71741
< 0.1%
68841
< 0.1%
67131
< 0.1%
65601
< 0.1%
60001
< 0.1%
58971
< 0.1%

BUN
Real number (ℝ≥0)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
MISSING

Distinct187
Distinct (%)0.5%
Missing2018
Missing (%)5.0%
Infinite0
Infinite (%)0.0%
Mean19.7710084
Minimum1
Maximum184
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size315.2 KiB
2021-11-29T11:27:26.323134image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile6
Q110
median15
Q323
95-th percentile52
Maximum184
Range183
Interquartile range (IQR)13

Descriptive statistics

Standard deviation16.45862674
Coefficient of variation (CV)0.8324626849
Kurtosis11.26213096
Mean19.7710084
Median Absolute Deviation (MAD)6
Skewness2.813857588
Sum757585.5
Variance270.8863941
MonotonicityNot monotonic
2021-11-29T11:27:26.423070image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
122183
 
5.4%
112183
 
5.4%
132172
 
5.4%
102067
 
5.1%
141972
 
4.9%
91901
 
4.7%
151809
 
4.5%
81689
 
4.2%
161576
 
3.9%
171525
 
3.8%
Other values (177)19241
47.7%
(Missing)2018
 
5.0%
ValueCountFrequency (%)
157
 
0.1%
2122
 
0.3%
2.51
 
< 0.1%
3325
 
0.8%
3.51
 
< 0.1%
4520
1.3%
4.52
 
< 0.1%
5823
2.0%
5.52
 
< 0.1%
61112
2.8%
ValueCountFrequency (%)
1841
< 0.1%
1771
< 0.1%
1731
< 0.1%
1702
< 0.1%
1691
< 0.1%
1651
< 0.1%
1621
< 0.1%
1611
< 0.1%
1601
< 0.1%
1591
< 0.1%

Alkalinephos
Real number (ℝ≥0)

MISSING

Distinct561
Distinct (%)4.0%
Missing26163
Missing (%)64.9%
Infinite0
Infinite (%)0.0%
Mean93.10953926
Minimum7
Maximum3619
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size315.2 KiB
2021-11-29T11:27:26.529278image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Quantile statistics

Minimum7
5-th percentile34
Q152
median70
Q3100
95-th percentile220
Maximum3619
Range3612
Interquartile range (IQR)48

Descriptive statistics

Standard deviation99.06438857
Coefficient of variation (CV)1.063955308
Kurtosis202.0913631
Mean93.10953926
Median Absolute Deviation (MAD)21
Skewness9.893273472
Sum1319641.5
Variance9813.753083
MonotonicityNot monotonic
2021-11-29T11:27:26.624539image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
58227
 
0.6%
56225
 
0.6%
52217
 
0.5%
49214
 
0.5%
54213
 
0.5%
53211
 
0.5%
61206
 
0.5%
50205
 
0.5%
46202
 
0.5%
55202
 
0.5%
Other values (551)12051
29.9%
(Missing)26163
64.9%
ValueCountFrequency (%)
71
 
< 0.1%
113
 
< 0.1%
122
 
< 0.1%
133
 
< 0.1%
144
 
< 0.1%
157
< 0.1%
168
< 0.1%
179
< 0.1%
1810
< 0.1%
1912
< 0.1%
ValueCountFrequency (%)
36191
< 0.1%
25281
< 0.1%
21011
< 0.1%
19191
< 0.1%
17761
< 0.1%
16691
< 0.1%
16502
< 0.1%
14371
< 0.1%
14361
< 0.1%
12141
< 0.1%

Calcium
Real number (ℝ≥0)

MISSING

Distinct340
Distinct (%)1.0%
Missing5339
Missing (%)13.2%
Infinite0
Infinite (%)0.0%
Mean7.403726319
Minimum1
Maximum27
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size315.2 KiB
2021-11-29T11:27:26.725551image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1.13
Q17.5
median8.2
Q38.6
95-th percentile9.3
Maximum27
Range26
Interquartile range (IQR)1.1

Descriptive statistics

Standard deviation2.394208939
Coefficient of variation (CV)0.3233789089
Kurtosis3.026393404
Mean7.403726319
Median Absolute Deviation (MAD)0.5
Skewness-1.809666996
Sum259108.21
Variance5.732236443
MonotonicityNot monotonic
2021-11-29T11:27:26.824137image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
8.31943
 
4.8%
8.21867
 
4.6%
8.41837
 
4.6%
8.51829
 
4.5%
8.11779
 
4.4%
8.61738
 
4.3%
81610
 
4.0%
7.91505
 
3.7%
8.71453
 
3.6%
8.81390
 
3.4%
Other values (330)18046
44.7%
(Missing)5339
 
13.2%
ValueCountFrequency (%)
152
 
0.1%
1.0155
 
0.1%
1.0274
0.2%
1.0371
0.2%
1.0493
0.2%
1.0578
0.2%
1.06113
0.3%
1.07108
0.3%
1.08155
0.4%
1.09169
0.4%
ValueCountFrequency (%)
271
 
< 0.1%
25.21
 
< 0.1%
23.71
 
< 0.1%
191
 
< 0.1%
18.82
 
< 0.1%
18.63
< 0.1%
18.24
< 0.1%
182
 
< 0.1%
17.85
< 0.1%
17.61
 
< 0.1%

Chloride
Real number (ℝ≥0)

MISSING

Distinct80
Distinct (%)0.4%
Missing18925
Missing (%)46.9%
Infinite0
Infinite (%)0.0%
Mean103.9236607
Minimum26
Maximum137
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size315.2 KiB
2021-11-29T11:27:26.998118image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Quantile statistics

Minimum26
5-th percentile95
Q1101
median104
Q3107
95-th percentile112
Maximum137
Range111
Interquartile range (IQR)6

Descriptive statistics

Standard deviation5.317791881
Coefficient of variation (CV)0.05117017475
Kurtosis5.220321269
Mean103.9236607
Median Absolute Deviation (MAD)3
Skewness-0.6957498632
Sum2225109.5
Variance28.27891048
MonotonicityNot monotonic
2021-11-29T11:27:27.093697image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1051909
 
4.7%
1041814
 
4.5%
1061799
 
4.5%
1031737
 
4.3%
1071640
 
4.1%
1021507
 
3.7%
1081326
 
3.3%
1011268
 
3.1%
1091095
 
2.7%
1001090
 
2.7%
Other values (70)6226
 
15.4%
(Missing)18925
46.9%
ValueCountFrequency (%)
261
 
< 0.1%
381
 
< 0.1%
631
 
< 0.1%
661
 
< 0.1%
701
 
< 0.1%
732
< 0.1%
742
< 0.1%
753
< 0.1%
763
< 0.1%
784
< 0.1%
ValueCountFrequency (%)
1371
 
< 0.1%
1331
 
< 0.1%
1321
 
< 0.1%
1311
 
< 0.1%
1302
 
< 0.1%
1291
 
< 0.1%
1282
 
< 0.1%
1272
 
< 0.1%
1252
 
< 0.1%
1249
< 0.1%

Creatinine
Real number (ℝ≥0)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
MISSING

Distinct1053
Distinct (%)2.8%
Missing2049
Missing (%)5.1%
Infinite0
Infinite (%)0.0%
Mean1.310148092
Minimum0.1
Maximum25.1
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size315.2 KiB
2021-11-29T11:27:27.192317image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Quantile statistics

Minimum0.1
5-th percentile0.47
Q10.68
median0.85
Q31.2
95-th percentile4.177
Maximum25.1
Range25
Interquartile range (IQR)0.52

Descriptive statistics

Standard deviation1.615869721
Coefficient of variation (CV)1.23334891
Kurtosis34.44470709
Mean1.310148092
Median Absolute Deviation (MAD)0.25
Skewness4.988954212
Sum50161.64
Variance2.611034954
MonotonicityNot monotonic
2021-11-29T11:27:27.296027image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.73071
 
7.6%
0.82853
 
7.1%
0.62602
 
6.5%
0.92086
 
5.2%
0.51863
 
4.6%
11538
 
3.8%
1.11070
 
2.7%
0.4876
 
2.2%
1.2818
 
2.0%
1.3604
 
1.5%
Other values (1043)20906
51.8%
(Missing)2049
 
5.1%
ValueCountFrequency (%)
0.118
 
< 0.1%
0.272
0.2%
0.211
 
< 0.1%
0.222
 
< 0.1%
0.231
 
< 0.1%
0.241
 
< 0.1%
0.251
 
< 0.1%
0.272
 
< 0.1%
0.285
 
< 0.1%
0.293
 
< 0.1%
ValueCountFrequency (%)
25.11
< 0.1%
251
< 0.1%
23.831
< 0.1%
23.711
< 0.1%
23.651
< 0.1%
22.961
< 0.1%
22.011
< 0.1%
21.971
< 0.1%
21.461
< 0.1%
21.311
< 0.1%

Bilirubin_direct
Real number (ℝ≥0)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
MISSING

Distinct204
Distinct (%)9.9%
Missing38279
Missing (%)94.9%
Infinite0
Infinite (%)0.0%
Mean1.168274186
Minimum0.01
Maximum37.5
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size315.2 KiB
2021-11-29T11:27:27.399035image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Quantile statistics

Minimum0.01
5-th percentile0.1
Q10.1
median0.3
Q30.9
95-th percentile5
Maximum37.5
Range37.49
Interquartile range (IQR)0.8

Descriptive statistics

Standard deviation2.859593602
Coefficient of variation (CV)2.447707599
Kurtosis44.43655636
Mean1.168274186
Median Absolute Deviation (MAD)0.2
Skewness5.810856783
Sum2403.14
Variance8.177275571
MonotonicityNot monotonic
2021-11-29T11:27:27.497303image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.1493
 
1.2%
0.2334
 
0.8%
0.3165
 
0.4%
0.4130
 
0.3%
0.570
 
0.2%
0.661
 
0.2%
0.744
 
0.1%
137
 
0.1%
0.833
 
0.1%
1.132
 
0.1%
Other values (194)658
 
1.6%
(Missing)38279
94.9%
ValueCountFrequency (%)
0.017
 
< 0.1%
0.024
 
< 0.1%
0.035
 
< 0.1%
0.044
 
< 0.1%
0.056
 
< 0.1%
0.066
 
< 0.1%
0.077
 
< 0.1%
0.084
 
< 0.1%
0.0911
 
< 0.1%
0.1493
1.2%
ValueCountFrequency (%)
37.51
< 0.1%
351
< 0.1%
301
< 0.1%
22.81
< 0.1%
22.21
< 0.1%
21.21
< 0.1%
211
< 0.1%
20.571
< 0.1%
202
< 0.1%
19.81
< 0.1%

Glucose
Real number (ℝ≥0)

MISSING

Distinct485
Distinct (%)1.3%
Missing1580
Missing (%)3.9%
Infinite0
Infinite (%)0.0%
Mean104.6776326
Minimum10
Maximum666
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size315.2 KiB
2021-11-29T11:27:27.601612image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Quantile statistics

Minimum10
5-th percentile65
Q186
median100
Q3117
95-th percentile159
Maximum666
Range656
Interquartile range (IQR)31

Descriptive statistics

Standard deviation31.97774388
Coefficient of variation (CV)0.3054878399
Kurtosis15.61004895
Mean104.6776326
Median Absolute Deviation (MAD)15
Skewness2.289946953
Sum4056886.33
Variance1022.576104
MonotonicityNot monotonic
2021-11-29T11:27:27.696254image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
97741
 
1.8%
95735
 
1.8%
100727
 
1.8%
96723
 
1.8%
90705
 
1.7%
98702
 
1.7%
93696
 
1.7%
94694
 
1.7%
91690
 
1.7%
88688
 
1.7%
Other values (475)31655
78.5%
(Missing)1580
 
3.9%
ValueCountFrequency (%)
101
 
< 0.1%
111
 
< 0.1%
131
 
< 0.1%
141
 
< 0.1%
151
 
< 0.1%
161
 
< 0.1%
171
 
< 0.1%
181
 
< 0.1%
192
< 0.1%
213
< 0.1%
ValueCountFrequency (%)
6661
< 0.1%
6511
< 0.1%
5631
< 0.1%
5011
< 0.1%
4721
< 0.1%
4342
< 0.1%
4201
< 0.1%
4181
< 0.1%
4152
< 0.1%
4091
< 0.1%

Lactate
Real number (ℝ≥0)

MISSING

Distinct575
Distinct (%)4.6%
Missing27843
Missing (%)69.0%
Infinite0
Infinite (%)0.0%
Mean1.712478988
Minimum0.2
Maximum26.9
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size315.2 KiB
2021-11-29T11:27:27.795121image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Quantile statistics

Minimum0.2
5-th percentile0.7
Q11
median1.4
Q31.9
95-th percentile3.6
Maximum26.9
Range26.7
Interquartile range (IQR)0.9

Descriptive statistics

Standard deviation1.385558634
Coefficient of variation (CV)0.8090952611
Kurtosis48.87845454
Mean1.712478988
Median Absolute Deviation (MAD)0.4
Skewness5.543861241
Sum21394
Variance1.919772729
MonotonicityNot monotonic
2021-11-29T11:27:27.894877image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1681
 
1.7%
1.2642
 
1.6%
0.9641
 
1.6%
1.1606
 
1.5%
1.3556
 
1.4%
0.8545
 
1.4%
1.4514
 
1.3%
1.6419
 
1.0%
1.5406
 
1.0%
0.7346
 
0.9%
Other values (565)7137
 
17.7%
(Missing)27843
69.0%
ValueCountFrequency (%)
0.21
 
< 0.1%
0.35
 
< 0.1%
0.371
 
< 0.1%
0.419
 
< 0.1%
0.461
 
< 0.1%
0.561
0.2%
0.533
 
< 0.1%
0.542
 
< 0.1%
0.553
 
< 0.1%
0.564
 
< 0.1%
ValueCountFrequency (%)
26.91
< 0.1%
22.41
< 0.1%
19.121
< 0.1%
17.81
< 0.1%
17.752
< 0.1%
17.51
< 0.1%
17.421
< 0.1%
17.41
< 0.1%
16.751
< 0.1%
16.71
< 0.1%

Magnesium
Real number (ℝ≥0)

MISSING

Distinct67
Distinct (%)0.2%
Missing4931
Missing (%)12.2%
Infinite0
Infinite (%)0.0%
Mean1.882682672
Minimum0.2
Maximum8.2
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size315.2 KiB
2021-11-29T11:27:27.993639image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Quantile statistics

Minimum0.2
5-th percentile1.4
Q11.7
median1.9
Q32.1
95-th percentile2.4
Maximum8.2
Range8
Interquartile range (IQR)0.4

Descriptive statistics

Standard deviation0.3329834783
Coefficient of variation (CV)0.1768664912
Kurtosis11.54294471
Mean1.882682672
Median Absolute Deviation (MAD)0.2
Skewness1.237828443
Sum66656.38
Variance0.1108779968
MonotonicityNot monotonic
2021-11-29T11:27:28.092105image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1.95306
13.2%
1.85150
12.8%
1.74155
10.3%
24154
10.3%
2.13158
7.8%
1.62977
7.4%
2.22149
5.3%
1.51922
 
4.8%
2.31399
 
3.5%
1.41163
 
2.9%
Other values (57)3872
9.6%
(Missing)4931
12.2%
ValueCountFrequency (%)
0.21
 
< 0.1%
0.52
 
< 0.1%
0.61
 
< 0.1%
0.76
 
< 0.1%
0.813
 
< 0.1%
0.940
 
0.1%
1115
 
0.3%
1.1195
0.5%
1.141
 
< 0.1%
1.2376
0.9%
ValueCountFrequency (%)
8.21
< 0.1%
6.52
< 0.1%
6.22
< 0.1%
61
< 0.1%
5.41
< 0.1%
5.11
< 0.1%
51
< 0.1%
4.92
< 0.1%
4.81
< 0.1%
4.61
< 0.1%

Phosphate
Real number (ℝ≥0)

HIGH CORRELATION
MISSING

Distinct141
Distinct (%)0.5%
Missing12015
Missing (%)29.8%
Infinite0
Infinite (%)0.0%
Mean3.221243953
Minimum0.2
Maximum13.5
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size315.2 KiB
2021-11-29T11:27:28.193635image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Quantile statistics

Minimum0.2
5-th percentile1.6
Q12.4
median3.1
Q33.8
95-th percentile5.4
Maximum13.5
Range13.3
Interquartile range (IQR)1.4

Descriptive statistics

Standard deviation1.23097838
Coefficient of variation (CV)0.3821437921
Kurtosis4.85223481
Mean3.221243953
Median Absolute Deviation (MAD)0.7
Skewness1.418484455
Sum91228.85
Variance1.515307771
MonotonicityNot monotonic
2021-11-29T11:27:28.301181image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
2.91168
 
2.9%
3.11145
 
2.8%
3.21124
 
2.8%
2.81121
 
2.8%
2.71120
 
2.8%
31078
 
2.7%
2.61058
 
2.6%
3.31050
 
2.6%
2.51019
 
2.5%
3.41008
 
2.5%
Other values (131)17430
43.2%
(Missing)12015
29.8%
ValueCountFrequency (%)
0.21
 
< 0.1%
0.35
 
< 0.1%
0.43
 
< 0.1%
0.511
 
< 0.1%
0.638
 
0.1%
0.740
 
0.1%
0.859
0.1%
0.851
 
< 0.1%
0.942
 
0.1%
1131
0.3%
ValueCountFrequency (%)
13.51
 
< 0.1%
12.91
 
< 0.1%
12.41
 
< 0.1%
12.31
 
< 0.1%
12.22
 
< 0.1%
12.11
 
< 0.1%
126
< 0.1%
11.81
 
< 0.1%
11.71
 
< 0.1%
11.61
 
< 0.1%

Potassium
Real number (ℝ≥0)

MISSING

Distinct250
Distinct (%)0.6%
Missing1867
Missing (%)4.6%
Infinite0
Infinite (%)0.0%
Mean3.809902519
Minimum1
Maximum9.8
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size315.2 KiB
2021-11-29T11:27:28.482501image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile3
Q13.5
median3.8
Q34.1
95-th percentile4.7
Maximum9.8
Range8.8
Interquartile range (IQR)0.6

Descriptive statistics

Standard deviation0.5150364389
Coefficient of variation (CV)0.1351836264
Kurtosis3.983847802
Mean3.809902519
Median Absolute Deviation (MAD)0.3
Skewness0.6604414302
Sum146563.14
Variance0.2652625334
MonotonicityNot monotonic
2021-11-29T11:27:28.578004image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
3.83446
 
8.5%
3.73405
 
8.4%
3.63202
 
7.9%
3.93152
 
7.8%
42696
 
6.7%
3.52696
 
6.7%
4.12344
 
5.8%
3.42328
 
5.8%
4.21891
 
4.7%
3.31824
 
4.5%
Other values (240)11485
28.5%
(Missing)1867
 
4.6%
ValueCountFrequency (%)
11
 
< 0.1%
1.33
 
< 0.1%
1.42
 
< 0.1%
1.52
 
< 0.1%
1.61
 
< 0.1%
1.72
 
< 0.1%
1.83
 
< 0.1%
1.910
< 0.1%
211
< 0.1%
2.116
< 0.1%
ValueCountFrequency (%)
9.81
 
< 0.1%
9.42
< 0.1%
9.22
< 0.1%
91
 
< 0.1%
8.21
 
< 0.1%
7.81
 
< 0.1%
7.63
< 0.1%
7.491
 
< 0.1%
7.42
< 0.1%
7.21
 
< 0.1%

Bilirubin_total
Real number (ℝ≥0)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
MISSING

Distinct256
Distinct (%)1.8%
Missing26088
Missing (%)64.7%
Infinite0
Infinite (%)0.0%
Mean1.324933324
Minimum0.1
Maximum49.2
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size315.2 KiB
2021-11-29T11:27:28.676214image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Quantile statistics

Minimum0.1
5-th percentile0.2
Q10.5
median0.7
Q31.2
95-th percentile3.7
Maximum49.2
Range49.1
Interquartile range (IQR)0.7

Descriptive statistics

Standard deviation2.783787126
Coefficient of variation (CV)2.101077145
Kurtosis83.56325878
Mean1.324933324
Median Absolute Deviation (MAD)0.3
Skewness8.049036374
Sum18877.65
Variance7.749470761
MonotonicityNot monotonic
2021-11-29T11:27:28.776727image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.51539
 
3.8%
0.41487
 
3.7%
0.61434
 
3.6%
0.71253
 
3.1%
0.31147
 
2.8%
0.81016
 
2.5%
0.9812
 
2.0%
1665
 
1.6%
0.2613
 
1.5%
1.1519
 
1.3%
Other values (246)3763
 
9.3%
(Missing)26088
64.7%
ValueCountFrequency (%)
0.1142
 
0.4%
0.151
 
< 0.1%
0.2613
 
1.5%
0.252
 
< 0.1%
0.31147
2.8%
0.352
 
< 0.1%
0.41487
3.7%
0.453
 
< 0.1%
0.51539
3.8%
0.552
 
< 0.1%
ValueCountFrequency (%)
49.21
< 0.1%
45.91
< 0.1%
44.91
< 0.1%
44.11
< 0.1%
43.51
< 0.1%
43.21
< 0.1%
40.61
< 0.1%
40.32
< 0.1%
40.12
< 0.1%
38.71
< 0.1%

TroponinI
Real number (ℝ≥0)

MISSING

Distinct1093
Distinct (%)15.5%
Missing33283
Missing (%)82.5%
Infinite0
Infinite (%)0.0%
Mean3.84627109
Minimum0.01
Maximum349.05
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size315.2 KiB
2021-11-29T11:27:28.880005image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Quantile statistics

Minimum0.01
5-th percentile0.01
Q10.03
median0.08
Q30.84
95-th percentile22.644
Maximum349.05
Range349.04
Interquartile range (IQR)0.81

Descriptive statistics

Standard deviation14.11725374
Coefficient of variation (CV)3.670374087
Kurtosis115.1912023
Mean3.84627109
Median Absolute Deviation (MAD)0.07
Skewness8.594489878
Sum27127.75
Variance199.2968533
MonotonicityNot monotonic
2021-11-29T11:27:28.978578image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.011342
 
3.3%
0.03894
 
2.2%
0.04334
 
0.8%
0.02332
 
0.8%
0.05215
 
0.5%
0.06188
 
0.5%
0.07160
 
0.4%
0.08126
 
0.3%
0.09111
 
0.3%
0.192
 
0.2%
Other values (1083)3259
 
8.1%
(Missing)33283
82.5%
ValueCountFrequency (%)
0.011342
3.3%
0.02332
 
0.8%
0.03894
2.2%
0.04334
 
0.8%
0.05215
 
0.5%
0.06188
 
0.5%
0.07160
 
0.4%
0.08126
 
0.3%
0.09111
 
0.3%
0.192
 
0.2%
ValueCountFrequency (%)
349.051
 
< 0.1%
219.621
 
< 0.1%
2005
< 0.1%
180.081
 
< 0.1%
1671
 
< 0.1%
164.531
 
< 0.1%
155.651
 
< 0.1%
153.341
 
< 0.1%
151.831
 
< 0.1%
149.341
 
< 0.1%

Hct
Real number (ℝ≥0)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
MISSING

Distinct557
Distinct (%)1.5%
Missing2317
Missing (%)5.7%
Infinite0
Infinite (%)0.0%
Mean30.36369499
Minimum5.5
Maximum66.2
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size315.2 KiB
2021-11-29T11:27:29.081830image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Quantile statistics

Minimum5.5
5-th percentile21
Q125.9
median29.9
Q334.6
95-th percentile41
Maximum66.2
Range60.7
Interquartile range (IQR)8.7

Descriptive statistics

Standard deviation6.173743692
Coefficient of variation (CV)0.2033264954
Kurtosis-0.01572534302
Mean30.36369499
Median Absolute Deviation (MAD)4.3
Skewness0.2924417642
Sum1154397.32
Variance38.11511117
MonotonicityNot monotonic
2021-11-29T11:27:29.175523image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
26380
 
0.9%
27330
 
0.8%
28306
 
0.8%
29302
 
0.7%
24294
 
0.7%
23292
 
0.7%
25291
 
0.7%
30291
 
0.7%
27.8255
 
0.6%
27.5253
 
0.6%
Other values (547)35025
86.8%
(Missing)2317
 
5.7%
ValueCountFrequency (%)
5.51
< 0.1%
71
< 0.1%
8.81
< 0.1%
9.11
< 0.1%
9.31
< 0.1%
9.41
< 0.1%
9.61
< 0.1%
9.71
< 0.1%
10.31
< 0.1%
10.71
< 0.1%
ValueCountFrequency (%)
66.21
< 0.1%
651
< 0.1%
63.41
< 0.1%
63.21
< 0.1%
61.71
< 0.1%
60.32
< 0.1%
58.81
< 0.1%
57.71
< 0.1%
56.12
< 0.1%
55.61
< 0.1%

Hgb
Real number (ℝ≥0)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
MISSING

Distinct253
Distinct (%)0.7%
Missing2448
Missing (%)6.1%
Infinite0
Infinite (%)0.0%
Mean10.20173775
Minimum2.2
Maximum26.6
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size315.2 KiB
2021-11-29T11:27:29.272501image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Quantile statistics

Minimum2.2
5-th percentile7
Q18.7
median10.1
Q311.6
95-th percentile13.8
Maximum26.6
Range24.4
Interquartile range (IQR)2.9

Descriptive statistics

Standard deviation2.090467689
Coefficient of variation (CV)0.204912902
Kurtosis0.3168065853
Mean10.20173775
Median Absolute Deviation (MAD)1.4
Skewness0.3436034238
Sum386523.44
Variance4.370055158
MonotonicityNot monotonic
2021-11-29T11:27:29.373221image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
9.4744
 
1.8%
9.2738
 
1.8%
9.5724
 
1.8%
9.9719
 
1.8%
9.8715
 
1.8%
9.7705
 
1.7%
9705
 
1.7%
10702
 
1.7%
10.5694
 
1.7%
9.1693
 
1.7%
Other values (243)30749
76.2%
(Missing)2448
 
6.1%
ValueCountFrequency (%)
2.21
< 0.1%
2.31
< 0.1%
2.61
< 0.1%
2.81
< 0.1%
2.91
< 0.1%
31
< 0.1%
3.11
< 0.1%
3.22
< 0.1%
3.62
< 0.1%
3.72
< 0.1%
ValueCountFrequency (%)
26.61
< 0.1%
24.82
< 0.1%
23.81
< 0.1%
23.41
< 0.1%
21.61
< 0.1%
21.21
< 0.1%
211
< 0.1%
20.61
< 0.1%
20.32
< 0.1%
19.61
< 0.1%

PTT
Real number (ℝ≥0)

MISSING

Distinct810
Distinct (%)4.0%
Missing20098
Missing (%)49.8%
Infinite0
Infinite (%)0.0%
Mean32.75607817
Minimum12.5
Maximum250
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size315.2 KiB
2021-11-29T11:27:29.471756image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Quantile statistics

Minimum12.5
5-th percentile22.4
Q126.2
median29.4
Q334.2
95-th percentile52.8
Maximum250
Range237.5
Interquartile range (IQR)8

Descriptive statistics

Standard deviation14.87619104
Coefficient of variation (CV)0.4541505536
Kurtosis67.33897588
Mean32.75607817
Median Absolute Deviation (MAD)3.7
Skewness6.568202019
Sum662917.51
Variance221.3010597
MonotonicityNot monotonic
2021-11-29T11:27:29.571889image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
27.7188
 
0.5%
28.1178
 
0.4%
27.6172
 
0.4%
28.5171
 
0.4%
28.7170
 
0.4%
26.7170
 
0.4%
28.6169
 
0.4%
27.5168
 
0.4%
27.3165
 
0.4%
26.2163
 
0.4%
Other values (800)18524
45.9%
(Missing)20098
49.8%
ValueCountFrequency (%)
12.51
 
< 0.1%
16.61
 
< 0.1%
17.13
< 0.1%
17.21
 
< 0.1%
17.31
 
< 0.1%
17.41
 
< 0.1%
17.51
 
< 0.1%
17.92
< 0.1%
18.13
< 0.1%
18.23
< 0.1%
ValueCountFrequency (%)
2503
 
< 0.1%
249.94
 
< 0.1%
24912
< 0.1%
237.51
 
< 0.1%
216.51
 
< 0.1%
212.31
 
< 0.1%
204.91
 
< 0.1%
200.81
 
< 0.1%
196.81
 
< 0.1%
195.51
 
< 0.1%

WBC
Real number (ℝ≥0)

MISSING

Distinct528
Distinct (%)1.4%
Missing2625
Missing (%)6.5%
Infinite0
Infinite (%)0.0%
Mean9.886976479
Minimum0.1
Maximum296.1
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size315.2 KiB
2021-11-29T11:27:29.674376image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Quantile statistics

Minimum0.1
5-th percentile4.1
Q16.8
median9.1
Q311.9
95-th percentile17.8
Maximum296.1
Range296
Interquartile range (IQR)5.1

Descriptive statistics

Standard deviation5.817755317
Coefficient of variation (CV)0.588426131
Kurtosis309.7728826
Mean9.886976479
Median Absolute Deviation (MAD)2.5
Skewness10.62723671
Sum372847.77
Variance33.84627693
MonotonicityNot monotonic
2021-11-29T11:27:29.768443image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
7.2466
 
1.2%
7.4451
 
1.1%
8443
 
1.1%
7.6438
 
1.1%
8.5431
 
1.1%
7.8429
 
1.1%
8.8426
 
1.1%
8.2424
 
1.1%
9.4422
 
1.0%
8.4419
 
1.0%
Other values (518)33362
82.7%
(Missing)2625
 
6.5%
ValueCountFrequency (%)
0.126
0.1%
0.214
< 0.1%
0.39
 
< 0.1%
0.411
< 0.1%
0.54
 
< 0.1%
0.68
 
< 0.1%
0.79
 
< 0.1%
0.83
 
< 0.1%
0.98
 
< 0.1%
113
< 0.1%
ValueCountFrequency (%)
296.11
< 0.1%
201.61
< 0.1%
180.41
< 0.1%
168.61
< 0.1%
152.91
< 0.1%
150.61
< 0.1%
144.91
< 0.1%
142.21
< 0.1%
140.41
< 0.1%
137.71
< 0.1%

Fibrinogen
Real number (ℝ≥0)

MISSING

Distinct708
Distinct (%)15.7%
Missing35821
Missing (%)88.8%
Infinite0
Infinite (%)0.0%
Mean283.0618162
Minimum34
Maximum1383
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size315.2 KiB
2021-11-29T11:27:29.942598image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Quantile statistics

Minimum34
5-th percentile104
Q1176
median238
Q3349
95-th percentile627.3
Maximum1383
Range1349
Interquartile range (IQR)173

Descriptive statistics

Standard deviation160.5263466
Coefficient of variation (CV)0.5671070325
Kurtosis2.999120798
Mean283.0618162
Median Absolute Deviation (MAD)78
Skewness1.532196777
Sum1278024.1
Variance25768.70794
MonotonicityNot monotonic
2021-11-29T11:27:30.046788image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
21741
 
0.1%
21431
 
0.1%
15131
 
0.1%
20229
 
0.1%
18527
 
0.1%
21926
 
0.1%
20025
 
0.1%
21524
 
0.1%
21324
 
0.1%
20324
 
0.1%
Other values (698)4233
 
10.5%
(Missing)35821
88.8%
ValueCountFrequency (%)
341
 
< 0.1%
359
< 0.1%
411
 
< 0.1%
422
 
< 0.1%
463
 
< 0.1%
482
 
< 0.1%
502
 
< 0.1%
512
 
< 0.1%
525
< 0.1%
52.51
 
< 0.1%
ValueCountFrequency (%)
13831
 
< 0.1%
12461
 
< 0.1%
11611
 
< 0.1%
10301
 
< 0.1%
10006
< 0.1%
9761
 
< 0.1%
9601
 
< 0.1%
9561
 
< 0.1%
9541
 
< 0.1%
9461
 
< 0.1%

Platelets
Real number (ℝ≥0)

MISSING

Distinct772
Distinct (%)2.0%
Missing2577
Missing (%)6.4%
Infinite0
Infinite (%)0.0%
Mean193.2062555
Minimum1
Maximum2322
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size315.2 KiB
2021-11-29T11:27:30.148588image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile67
Q1129
median179
Q3239
95-th percentile363
Maximum2322
Range2321
Interquartile range (IQR)110

Descriptive statistics

Standard deviation98.16312389
Coefficient of variation (CV)0.5080742529
Kurtosis13.21220267
Mean193.2062555
Median Absolute Deviation (MAD)54
Skewness1.92145052
Sum7295275
Variance9635.998892
MonotonicityNot monotonic
2021-11-29T11:27:30.244349image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
180213
 
0.5%
166209
 
0.5%
158209
 
0.5%
159208
 
0.5%
162207
 
0.5%
170206
 
0.5%
168203
 
0.5%
160203
 
0.5%
182203
 
0.5%
141202
 
0.5%
Other values (762)35696
88.5%
(Missing)2577
 
6.4%
ValueCountFrequency (%)
11
 
< 0.1%
24
< 0.1%
32
 
< 0.1%
47
< 0.1%
57
< 0.1%
63
< 0.1%
77
< 0.1%
84
< 0.1%
95
< 0.1%
104
< 0.1%
ValueCountFrequency (%)
23221
< 0.1%
15921
< 0.1%
14211
< 0.1%
13431
< 0.1%
12621
< 0.1%
11421
< 0.1%
10241
< 0.1%
10071
< 0.1%
9921
< 0.1%
9841
< 0.1%

Age
Real number (ℝ≥0)

Distinct5987
Distinct (%)14.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean61.64342324
Minimum14
Maximum100
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size315.2 KiB
2021-11-29T11:27:30.342906image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Quantile statistics

Minimum14
5-th percentile30
Q151
median63.11
Q374
95-th percentile85
Maximum100
Range86
Interquartile range (IQR)23

Descriptive statistics

Standard deviation16.48294561
Coefficient of variation (CV)0.2673917954
Kurtosis-0.2334728394
Mean61.64342324
Median Absolute Deviation (MAD)11.27
Skewness-0.4250999292
Sum2486449.12
Variance271.6874961
MonotonicityNot monotonic
2021-11-29T11:27:30.441123image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
67581
 
1.4%
68545
 
1.4%
66521
 
1.3%
65512
 
1.3%
61502
 
1.2%
69498
 
1.2%
71490
 
1.2%
62480
 
1.2%
70478
 
1.2%
63473
 
1.2%
Other values (5977)35256
87.4%
ValueCountFrequency (%)
142
 
< 0.1%
152
 
< 0.1%
165
 
< 0.1%
1713
< 0.1%
1832
0.1%
18.113
 
< 0.1%
18.131
 
< 0.1%
18.142
 
< 0.1%
18.151
 
< 0.1%
18.181
 
< 0.1%
ValueCountFrequency (%)
100392
1.0%
89112
 
0.3%
88.991
 
< 0.1%
88.982
 
< 0.1%
88.974
 
< 0.1%
88.961
 
< 0.1%
88.954
 
< 0.1%
88.942
 
< 0.1%
88.931
 
< 0.1%
88.925
 
< 0.1%

Gender
Categorical

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size315.2 KiB
1
22566 
0
17770 

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters40336
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row1

Common Values

ValueCountFrequency (%)
122566
55.9%
017770
44.1%

Length

2021-11-29T11:27:30.536556image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
Histogram of lengths of the category

Pie chart

2021-11-29T11:27:30.590770image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
ValueCountFrequency (%)
122566
55.9%
017770
44.1%

Most occurring characters

ValueCountFrequency (%)
122566
55.9%
017770
44.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number40336
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
122566
55.9%
017770
44.1%

Most occurring scripts

ValueCountFrequency (%)
Common40336
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
122566
55.9%
017770
44.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII40336
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
122566
55.9%
017770
44.1%

Unit1
Categorical

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
MISSING

Distinct2
Distinct (%)< 0.1%
Missing15617
Missing (%)38.7%
Memory size315.2 KiB
0.0
12452 
1.0
12267 

Length

Max length3
Median length3
Mean length3
Min length3

Characters and Unicode

Total characters74157
Distinct characters3
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0.0
2nd row1.0
3rd row0.0
4th row1.0
5th row1.0

Common Values

ValueCountFrequency (%)
0.012452
30.9%
1.012267
30.4%
(Missing)15617
38.7%

Length

2021-11-29T11:27:30.643284image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
Histogram of lengths of the category

Pie chart

2021-11-29T11:27:30.693602image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
ValueCountFrequency (%)
0.012452
50.4%
1.012267
49.6%

Most occurring characters

ValueCountFrequency (%)
037171
50.1%
.24719
33.3%
112267
 
16.5%

Most occurring categories

ValueCountFrequency (%)
Decimal Number49438
66.7%
Other Punctuation24719
33.3%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
037171
75.2%
112267
 
24.8%
Other Punctuation
ValueCountFrequency (%)
.24719
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common74157
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
037171
50.1%
.24719
33.3%
112267
 
16.5%

Most occurring blocks

ValueCountFrequency (%)
ASCII74157
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
037171
50.1%
.24719
33.3%
112267
 
16.5%

Unit2
Categorical

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
MISSING

Distinct2
Distinct (%)< 0.1%
Missing15617
Missing (%)38.7%
Memory size315.2 KiB
1.0
12452 
0.0
12267 

Length

Max length3
Median length3
Mean length3
Min length3

Characters and Unicode

Total characters74157
Distinct characters3
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row1.0
2nd row0.0
3rd row1.0
4th row0.0
5th row0.0

Common Values

ValueCountFrequency (%)
1.012452
30.9%
0.012267
30.4%
(Missing)15617
38.7%

Length

2021-11-29T11:27:30.746871image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
Histogram of lengths of the category

Pie chart

2021-11-29T11:27:30.797666image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
ValueCountFrequency (%)
1.012452
50.4%
0.012267
49.6%

Most occurring characters

ValueCountFrequency (%)
036986
49.9%
.24719
33.3%
112452
 
16.8%

Most occurring categories

ValueCountFrequency (%)
Decimal Number49438
66.7%
Other Punctuation24719
33.3%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
036986
74.8%
112452
 
25.2%
Other Punctuation
ValueCountFrequency (%)
.24719
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common74157
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
036986
49.9%
.24719
33.3%
112452
 
16.8%

Most occurring blocks

ValueCountFrequency (%)
ASCII74157
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
036986
49.9%
.24719
33.3%
112452
 
16.8%

HospAdmTime
Real number (ℝ)

ZEROS

Distinct12156
Distinct (%)30.1%
Missing1
Missing (%)< 0.1%
Infinite0
Infinite (%)0.0%
Mean-51.84894508
Minimum-5366.86
Maximum23.99
Zeros1313
Zeros (%)3.3%
Negative38767
Negative (%)96.1%
Memory size315.2 KiB
2021-11-29T11:27:30.860666image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Quantile statistics

Minimum-5366.86
5-th percentile-240.942
Q1-43.685
median-6.05
Q3-0.04
95-th percentile-0.01
Maximum23.99
Range5390.85
Interquartile range (IQR)43.645

Descriptive statistics

Standard deviation139.766452
Coefficient of variation (CV)-2.695646975
Kurtosis175.3735088
Mean-51.84894508
Median Absolute Deviation (MAD)6.03
Skewness-9.578944604
Sum-2091327.2
Variance19534.6611
MonotonicityNot monotonic
2021-11-29T11:27:30.965424image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
-0.023999
 
9.9%
-0.032487
 
6.2%
01313
 
3.3%
-0.011293
 
3.2%
-0.04794
 
2.0%
-0.05436
 
1.1%
-0.06241
 
0.6%
-0.07176
 
0.4%
-0.09108
 
0.3%
-0.0899
 
0.2%
Other values (12146)29389
72.9%
ValueCountFrequency (%)
-5366.861
< 0.1%
-3710.661
< 0.1%
-3397.641
< 0.1%
-3342.341
< 0.1%
-3322.91
< 0.1%
-3269.11
< 0.1%
-3212.561
< 0.1%
-3189.391
< 0.1%
-3141.551
< 0.1%
-3112.121
< 0.1%
ValueCountFrequency (%)
23.991
< 0.1%
22.041
< 0.1%
20.041
< 0.1%
17.341
< 0.1%
16.021
< 0.1%
14.651
< 0.1%
14.211
< 0.1%
141
< 0.1%
11.941
< 0.1%
10.991
< 0.1%

ICULOS
Real number (ℝ≥0)

SKEWED

Distinct31
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1.528113844
Minimum1
Maximum304
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size315.2 KiB
2021-11-29T11:27:31.062150image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q11
median1
Q31
95-th percentile4
Maximum304
Range303
Interquartile range (IQR)0

Descriptive statistics

Standard deviation2.806393199
Coefficient of variation (CV)1.836507935
Kurtosis7866.580249
Mean1.528113844
Median Absolute Deviation (MAD)0
Skewness77.93149665
Sum61638
Variance7.875842789
MonotonicityNot monotonic
2021-11-29T11:27:31.146709image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
Histogram with fixed size bins (bins=31)
ValueCountFrequency (%)
131543
78.2%
24129
 
10.2%
31897
 
4.7%
41149
 
2.8%
5653
 
1.6%
6423
 
1.0%
7233
 
0.6%
8123
 
0.3%
967
 
0.2%
1032
 
0.1%
Other values (21)87
 
0.2%
ValueCountFrequency (%)
131543
78.2%
24129
 
10.2%
31897
 
4.7%
41149
 
2.8%
5653
 
1.6%
6423
 
1.0%
7233
 
0.6%
8123
 
0.3%
967
 
0.2%
1032
 
0.1%
ValueCountFrequency (%)
3041
 
< 0.1%
2821
 
< 0.1%
2691
 
< 0.1%
304
< 0.1%
281
 
< 0.1%
272
< 0.1%
263
< 0.1%
252
< 0.1%
241
 
< 0.1%
234
< 0.1%

SepsisLabel
Categorical

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size315.2 KiB
0
39910 
1
 
426

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters40336
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
039910
98.9%
1426
 
1.1%

Length

2021-11-29T11:27:31.240702image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
Histogram of lengths of the category

Pie chart

2021-11-29T11:27:31.369286image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
ValueCountFrequency (%)
039910
98.9%
1426
 
1.1%

Most occurring characters

ValueCountFrequency (%)
039910
98.9%
1426
 
1.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number40336
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
039910
98.9%
1426
 
1.1%

Most occurring scripts

ValueCountFrequency (%)
Common40336
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
039910
98.9%
1426
 
1.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII40336
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
039910
98.9%
1426
 
1.1%

Sepsis
Categorical

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size315.2 KiB
0
37404 
1
 
2932

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters40336
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
037404
92.7%
12932
 
7.3%

Length

2021-11-29T11:27:31.425646image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
Histogram of lengths of the category

Pie chart

2021-11-29T11:27:31.481501image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
ValueCountFrequency (%)
037404
92.7%
12932
 
7.3%

Most occurring characters

ValueCountFrequency (%)
037404
92.7%
12932
 
7.3%

Most occurring categories

ValueCountFrequency (%)
Decimal Number40336
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
037404
92.7%
12932
 
7.3%

Most occurring scripts

ValueCountFrequency (%)
Common40336
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
037404
92.7%
12932
 
7.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII40336
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
037404
92.7%
12932
 
7.3%

Hours
Real number (ℝ≥0)

Distinct273
Distinct (%)0.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean38.48200119
Minimum8
Maximum336
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size315.2 KiB
2021-11-29T11:27:31.544088image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Quantile statistics

Minimum8
5-th percentile14
Q124
median38
Q347
95-th percentile58
Maximum336
Range328
Interquartile range (IQR)23

Descriptive statistics

Standard deviation22.79592332
Coefficient of variation (CV)0.5923788425
Kurtosis42.42147962
Mean38.48200119
Median Absolute Deviation (MAD)11
Skewness4.840449261
Sum1552210
Variance519.6541201
MonotonicityNot monotonic
2021-11-29T11:27:31.644911image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
361364
 
3.4%
391362
 
3.4%
381323
 
3.3%
401285
 
3.2%
411271
 
3.2%
371223
 
3.0%
431210
 
3.0%
421193
 
3.0%
441143
 
2.8%
451089
 
2.7%
Other values (263)27873
69.1%
ValueCountFrequency (%)
8328
0.8%
9236
 
0.6%
10221
 
0.5%
11234
 
0.6%
12285
 
0.7%
13350
0.9%
14412
1.0%
15536
1.3%
16601
1.5%
17721
1.8%
ValueCountFrequency (%)
33610
< 0.1%
3353
 
< 0.1%
3342
 
< 0.1%
3331
 
< 0.1%
3301
 
< 0.1%
3281
 
< 0.1%
3271
 
< 0.1%
3261
 
< 0.1%
3201
 
< 0.1%
3181
 
< 0.1%

Interactions

2021-11-29T11:27:19.577855image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2021-11-29T11:27:15.944317image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2021-11-29T11:27:16.044204image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2021-11-29T11:27:16.139724image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2021-11-29T11:27:16.237429image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2021-11-29T11:27:16.337504image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2021-11-29T11:27:16.430849image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2021-11-29T11:27:16.523277image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2021-11-29T11:27:16.614241image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2021-11-29T11:27:16.775691image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2021-11-29T11:27:16.861829image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2021-11-29T11:27:16.951598image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2021-11-29T11:27:17.040444image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2021-11-29T11:27:17.131837image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2021-11-29T11:27:17.220973image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2021-11-29T11:27:17.307361image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2021-11-29T11:27:17.401194image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2021-11-29T11:27:17.490615image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2021-11-29T11:27:17.582415image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2021-11-29T11:27:17.680262image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2021-11-29T11:27:17.769214image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2021-11-29T11:27:17.860951image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2021-11-29T11:27:17.948030image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2021-11-29T11:27:18.044106image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2021-11-29T11:27:18.135872image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2021-11-29T11:27:18.226452image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2021-11-29T11:27:18.320765image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2021-11-29T11:27:18.415386image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2021-11-29T11:27:18.501497image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2021-11-29T11:27:18.590169image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2021-11-29T11:27:18.686044image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2021-11-29T11:27:18.776269image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2021-11-29T11:27:18.936309image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2021-11-29T11:27:19.025224image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2021-11-29T11:27:19.114287image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2021-11-29T11:27:19.211249image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2021-11-29T11:27:19.302000image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2021-11-29T11:27:19.390378image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2021-11-29T11:27:19.484454image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Correlations

2021-11-29T11:27:31.792998image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Spearman's ρ

The Spearman's rank correlation coefficient (ρ) is a measure of monotonic correlation between two variables, and is therefore better in catching nonlinear monotonic correlations than Pearson's r. It's value lies between -1 and +1, -1 indicating total negative monotonic correlation, 0 indicating no monotonic correlation and 1 indicating total positive monotonic correlation.

To calculate ρ for two variables X and Y, one divides the covariance of the rank variables of X and Y by the product of their standard deviations.
2021-11-29T11:27:32.139320image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Pearson's r

The Pearson's correlation coefficient (r) is a measure of linear correlation between two variables. It's value lies between -1 and +1, -1 indicating total negative linear correlation, 0 indicating no linear correlation and 1 indicating total positive linear correlation. Furthermore, r is invariant under separate changes in location and scale of the two variables, implying that for a linear function the angle to the x-axis does not affect r.

To calculate r for two variables X and Y, one divides the covariance of X and Y by the product of their standard deviations.
2021-11-29T11:27:32.482128image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Kendall's τ

Similarly to Spearman's rank correlation coefficient, the Kendall rank correlation coefficient (τ) measures ordinal association between two variables. It's value lies between -1 and +1, -1 indicating total negative correlation, 0 indicating no correlation and 1 indicating total positive correlation.

To calculate τ for two variables X and Y, one determines the number of concordant and discordant pairs of observations. τ is given by the number of concordant pairs minus the discordant pairs divided by the total number of pairs.
2021-11-29T11:27:32.769645image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Cramér's V (φc)

Cramér's V is an association measure for nominal random variables. The coefficient ranges from 0 to 1, with 0 indicating independence and 1 indicating perfect association. The empirical estimators used for Cramér's V have been proved to be biased, even for large samples. We use a bias-corrected measure that has been proposed by Bergsma in 2013 that can be found here.

Missing values

2021-11-29T11:27:19.822723image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
A simple visualization of nullity by column.
2021-11-29T11:27:20.949657image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
Nullity matrix is a data-dense display which lets you quickly visually pick out patterns in data completion.
2021-11-29T11:27:21.836789image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
The correlation heatmap measures nullity correlation: how strongly the presence or absence of one variable affects the presence of another.
2021-11-29T11:27:22.692558image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
The dendrogram allows you to more fully correlate variable completion, revealing trends deeper than the pairwise ones visible in the correlation heatmap.

Sample

First rows

PatientIDHRO2SatTempSBPMAPDBPRespEtCO2BaseExcessHCO3FiO2pHPaCO2SaO2ASTBUNAlkalinephosCalciumChlorideCreatinineBilirubin_directGlucoseLactateMagnesiumPhosphatePotassiumBilirubin_totalTroponinIHctHgbPTTWBCFibrinogenPlateletsAgeGenderUnit1Unit2HospAdmTimeICULOSSepsisLabelSepsisHours
0176.085.036.1178.044.00NaN17.0NaN18.045.00.257.3186.078.016.014.098.09.385.00.7NaN133.0NaN2.03.33.80.3NaN36.212.2NaN5.7NaN317.083.140NaNNaN-0.0310054
1254.094.036.00114.050.5036.09.0NaNNaN22.0NaNNaNNaNNaNNaN100.0NaN7.9113.02.5NaN78.0NaN2.54.45.1NaNNaN27.89.7NaN11.0NaN158.075.9100.01.0-98.6010023
2368.091.036.89122.062.6744.017.0NaN5.029.00.507.4938.0NaNNaN25.0NaN10.998.00.8NaN51.0NaN2.42.33.4NaNNaN26.28.829.58.3NaN465.045.8201.00.0-1195.7110048
3493.095.536.0690.034.0044.014.0NaN0.022.0NaN7.3641.097.5NaN14.0NaN8.2105.00.8NaN69.0NaN1.73.84.0NaNNaN24.08.321.37.6NaN144.065.7100.01.0-8.7710029
4561.096.036.22114.073.00NaN14.0NaNNaN24.0NaNNaNNaNNaN16.06.062.07.8105.00.6NaN103.0NaN1.92.83.10.5NaN39.714.229.04.7NaN273.028.0911.00.0-0.0520048
5687.095.036.33101.073.00NaN18.5NaN0.029.00.407.3447.0NaNNaN9.0NaNNaN111.00.7NaN68.01.4NaNNaN3.8NaNNaN36.912.2NaN12.0NaN298.052.0111.00.0-0.0330017
67103.093.037.2891.059.0045.012.0NaN-12.013.00.407.2223.0NaN452.052.088.05.9111.03.5NaN71.02.21.60.92.81.4NaN36.714.525.47.2NaN26.064.2411.00.0-0.0510045
7865.079.035.6789.057.0040.012.0NaN-11.015.0NaN7.2722.0NaNNaN27.0NaN7.4105.01.1NaN84.00.81.82.73.2NaNNaN25.08.6NaN9.0NaN205.087.081NaNNaN-2.2310040
8985.089.535.3378.056.0044.013.0NaN-7.023.00.357.1332.074.0NaN11.0NaN7.4103.00.7NaN87.00.81.11.73.0NaNNaN21.87.324.23.9124.064.027.921NaNNaN-0.03101258
91063.090.035.5097.063.0047.010.0NaN-3.023.00.407.3237.096.0NaN17.0NaNNaN105.00.9NaN92.01.12.1NaN3.7NaNNaN27.99.529.98.7NaN107.076.7100.01.0-2.3630023

Last rows

PatientIDHRO2SatTempSBPMAPDBPRespEtCO2BaseExcessHCO3FiO2pHPaCO2SaO2ASTBUNAlkalinephosCalciumChlorideCreatinineBilirubin_directGlucoseLactateMagnesiumPhosphatePotassiumBilirubin_totalTroponinIHctHgbPTTWBCFibrinogenPlateletsAgeGenderUnit1Unit2HospAdmTimeICULOSSepsisLabelSepsisHours
4032611999162.092.035.1111.072.044.010.031.0NaNNaNNaNNaNNaNNaNNaN14.0NaN7.50NaN0.79NaN90.0NaN1.6NaN4.1NaNNaN26.38.4NaN6.4NaN96.081.000.01.0-66.1310025
4032711999284.086.535.9116.075.056.015.0NaNNaNNaNNaNNaNNaNNaNNaN37.0NaN9.20NaN9.93NaN97.0NaN1.86.64.5NaN0.4130.29.5NaN2.8NaN198.045.011.00.0-4.5510041
4032811999378.092.036.0121.081.056.016.0NaNNaNNaNNaNNaNNaNNaNNaN15.0NaN8.30NaN1.01NaN132.0NaN2.02.64.1NaN0.0142.014.9NaN12.3NaN175.065.01NaNNaN-3.5310021
4032911999468.093.035.495.068.048.012.026.0NaNNaN0.47.2528.097.2NaN11.0NaN1.02NaN1.03NaN104.02.251.93.63.6NaNNaN30.310.2NaN7.2NaN62.071.010.01.0-29.5710042
4033011999554.092.035.4128.088.066.013.0NaNNaNNaNNaNNaNNaNNaNNaN9.0NaN8.80NaN0.81NaN86.0NaN2.03.03.5NaNNaN39.213.1NaN7.0289.0154.076.010.01.0-14.9010042
4033111999669.095.035.781.060.043.016.0NaNNaNNaNNaNNaNNaNNaN849.04.0259.08.70NaN0.41NaN135.0NaN1.6NaN3.33.30.0142.713.8NaN12.6NaN238.084.00NaNNaN-6.6910048
4033211999744.089.036.397.063.047.014.045.0NaNNaNNaNNaNNaNNaN24.05.0116.09.80NaN0.690.1101.5NaN3.13.13.10.71.0944.015.038.210.0NaN177.030.01NaNNaN-0.0210025
4033311999857.088.036.0119.079.055.017.0NaNNaNNaNNaNNaNNaNNaN9.049.068.07.80NaN6.60NaN83.0NaN1.94.14.20.2NaN26.18.0NaN10.7NaN179.060.001.00.0-53.6410049
4033411999987.083.037.2128.090.066.017.0NaNNaNNaNNaNNaNNaNNaN33.028.049.08.40NaN0.98NaN108.0NaNNaNNaN3.40.9NaN19.16.5NaN10.0NaN255.084.001.00.0-10.7410020
4033512000072.096.036.4110.078.058.015.0NaNNaNNaNNaNNaNNaNNaN18.09.075.08.90NaN0.530.1123.0NaN2.24.03.30.9NaN37.111.629.15.4NaN216.062.00NaNNaN0.0010035